Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add mrpulor-gh/nuphus --skill agent-orchestrationgit clone --depth 1 https://github.com/mrpulor-gh/nuphusWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mrpulor-gh/nuphus/agent-orchestration)<a href="https://agentmods.dev/skills/mrpulor-gh/nuphus/agent-orchestration"><img src="https://agentmods.dev/badge/skills/mrpulor-gh/nuphus/agent-orchestration/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mrpulor-gh/nuphus/agent-orchestration"><img src="https://agentmods.dev/badge/skills/mrpulor-gh/nuphus/agent-orchestration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.07921 |
| Opus 5.5 | $0.00000 | $0.03168 |
| Sonnet 5.5 | $0.00000 | $0.01584 |
| Haiku 4.5 | $0.00000 | $0.00792 |
Grade A, and why
agent-orchestration scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- 终端类:curl 直调;**PowerShell 必须发 UTF-8 字节体**(`-Body ([Text.Encoding]::UTF8.GetBytes($json))`),字符串 body 会把中文压成 `?`(实测);纯 ASCII body 才可用单引号直传 How it starts
The opening of the file, as written. The whole thing — 328 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent 平台编排
外部 Agent(独立终端 TUI / 桌面 App / Web 等平台)协作指南。系统提示词已覆盖的(工具描述/annotation/Constitution)不重复,本技能只写外部 Agent 特有流程。
铁律:非显式指定不派发外部 Agent。
1. 登记(team.toml)
渐进登记:每用一个外部 Agent,在 plugin/team.toml 追加一段。只记稳定事实(mode/launch/process/window_hint/dispatch_steps/note);PID/hwnd 每次启动必变、hwnd 会被 OS 复用给无关窗口——一律按当次实况重新解析,禁止写死。
本段只示格式(键名与注释);字段值一律占位,不代表任何已登记 agent 的实况。 任何具体 agent 的字段值,一律以
plugin/team.toml当次读取为准。 完整段示例(含 dispatch_steps)见本节末尾第 3 条,此处不重复。
双登记路径(实测均有效):
- 手改 team.toml:直接编辑保存即可被运行中系统即时读取(无需重启),适合快速实验与本轮临时接入;
- 配置中心录入:桌面 设置 → 外部 Agent → 新增(走
upsert_external_agent),适合正式归档——会联动生成 handoff 工作目录(read.md/memory.md/status.json),手改路径不生成这些文件(须后续补agent_init或由首次 dispatch 补建空骨架)。
调用决策:Read team.toml → process_list 看谁活着(活着优先)→ 按平台能力匹配。不维护历史评分。
跑通即归档(强制,当轮完成)
新外部 Agent 首次跑通验证后,必须当轮登记归档,禁止「以后再用再配」——不归档则下次会话无从知晓其存在与用法,跑通经验直接丢失。
- 配置中心录入:桌面 设置 → 外部 Agent → 新增(走
upsert_external_agent):- 派发必需:
key(唯一、保存后不可改)/mode(窗口分类依据,§2 交互方式由此决定)/launch+args(§2 启动 SOP 手动启动用)/window_hint(终端类标题常被覆写,选稳定前缀)/process(process_list 识别依赖此字段)/dispatch_steps(§1.1——配错一步指令就打不进去,第一责任区) - 人读与备忘:
display_name/icon/description(description 会同步为该 agent read.md 的职责段);note= Leader 专属实测备忘(随配置读取、派发结果回显、UI 禁编辑)——opencode 的「window_hint 扫描无效、走 pid 路径」结论就记在这里
已废弃不生效:
cooldown_secs/await_timeout_secs/timeout_action/timeout_script/auto_approve/auto_approve_script/confirm_keywords——早期设想均未落地,配了等同没配,不要依赖(后端仅为旧配置兼容解析,UI 不再提供录入)。字段全集以代码为准:AgentFields(src-tauri/src/commands/config/team.rs)。 - 派发必需:
- 落盘核对:
plugin/team.toml出现该段且原有段未被破坏(写回是段级增量);新 key 联动生成 handoff 工作目录。 - 完整段示例(全量字段的格式示例;值一律占位,实况以
plugin/team.toml为准):
[{key}]
mode = "embedded" # background | embedded | standalone | web
display_name = "<显示名>"
icon = "terminal"
launch = "<启动命令>"
window_hint = "<窗口特征>"
process = "<进程名>"
note = "<Leader 实测备忘>(Leader 专属,UI 不可编辑)"
[[{key}.dispatch_steps]]
tool = "desktop_window_activate"
with = { hwnd = "{hwnd}" }
[[{key}.dispatch_steps]]
tool = "__sleep"
with = { ms = 500 }
[[{key}.dispatch_steps]]
tool = "desktop_input"
with = { hwnd = "{hwnd}", mode = "type", text = "{message}", send = "none" }
[[{key}.dispatch_steps]]
tool = "desktop_input"
with = { hwnd = "{hwnd}", mode = "hotkey", keys = ["enter"] }
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago Changed · +3 lines 2c51d7d6534a
- 24d ago Changed 9fd87805dede
- 26d ago Changed 87a8b23af8d1
- 27d ago Changed · -32 lines 5d9ce2e25668
- 1mo ago Changed · +2 lines 5e5183fc6ba7
- 1mo ago Changed · +5 lines a37bac260e59
- 1mo ago First seen · 350 lines · 0 tokens per session scan A d7f66500cdf3
agent-orchestration is a skill published in the GitHub repository mrpulor-gh/nuphus (89 stars, last pushed today), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 7,921 tokens. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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